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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Semiparametric modeling of grouped current duration data with preferential reporting.

Alexander C McLain1, Rajeshwari Sundaram, Marie Thoma

  • 1Department of Epidemiology and Biostatistics, University of South Carolina, 915 Greene Street, Columbia, SC 29208, U.S.A.

Statistics in Medicine
|May 28, 2014
PubMed
Summary

This study addresses length-biased current duration data from surveys. New semiparametric and piecewise models improve analysis of pregnancy attempt durations, accounting for digit preference.

Keywords:
backwards recurrence timescurrent durationdigit preferencegrouped survival dataproportional hazards model

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Demography

Background:

  • Current duration data in cross-sectional studies are often length-biased.
  • Women attempting pregnancy are more likely to report longer durations.
  • Existing analysis methods have limitations.

Purpose of the Study:

  • To propose novel statistical models for analyzing grouped current duration data.
  • To address length-bias and digit preference in duration analysis.
  • To analyze current duration data from the 2002 National Survey of Family Growth.

Main Methods:

  • Developed a semiparametric Cox model.
  • Incorporated a piecewise constant baseline model to handle digit preference.
  • Conducted simulation studies to assess robustness.

Main Results:

  • The proposed models effectively analyze grouped current duration data.
  • The methods demonstrate robustness in the presence of digit preference.
  • Analysis of 2002 National Survey of Family Growth data was performed.

Conclusions:

  • The novel semiparametric and piecewise models offer improved analysis of length-biased duration data.
  • These methods are valuable for understanding time-related events in surveys.
  • The findings contribute to robust statistical analysis in public health research.